1. Addressing Appropriate Criteria in Design: A Blend of Organization Consciousness and Awareness Kemper Lewis Associate Professor Department of Mechanical and Aerospace Engineering University at Buffalo

2. Frame of Reference: A Model of Learning Don’t know you don’t know INCOMPETENT UNCONSCIOUS Don’t know you know Know you don’t know Know you know CONSCIOUS COMPETENT

3. Capturing Preferences in Design: States of Consciousness Don’t know they don’t know ENTERPRISE UNAWARENESS ORGANIZATIONAL UNCONSCIOUS Don’t know they know Know they don’t know Know they know ORGANIZATIONAL CONSCIOUS ENTERPRISE AWARENESS Common practice: Use decision tools that give answers Common practice: Use decision tools with some recognition of limitation Common practice: Use decision tools with common goal Common practice: Use decision tools with common goal

4. Capturing Preferences in Design: Decision Making Don’t know they don’t know ENTERPRISE UNAWARENESS ORGANIZATIONAL UNCONSCIOUS Don’t know they know Know they don’t know Know they know ORGANIZATIONAL CONSCIOUS ENTERPRISE AWARENESS Multicriteria decision making under certainty Multicriteria decision making under uncertainty Single criteria decision making under un/certainty

5. Capturing Preferences in Design: Game Playing Multicriteria decision making under certainty ENTERPRISE UNAWARENESS ORGANIZATIONAL UNCONSCIOUS Single criteria decision making under un/certainty Multicriteria decision making under uncertainty Single criteria decision making under un/certainty ORGANIZATIONAL CONSCIOUS ENTERPRISE AWARENESS Pareto Sets Sequential Processes Bargaining Coalitions Noncooperative Leader/Follower Pareto Sets Coalitions Cooperative Coalitions Cooperative Coalitions

6. Research Issues ENTERPRISE UNAWARENESS ORGANIZATIONAL UNCONSCIOUS ORGANIZATIONAL CONSCIOUS ENTERPRISE AWARENESS ð Group vs. Individual Rationality ð Bargaining and Coalitions ð Demand/Profit Prediction ð Corporate attitudes ð Dynamic markets ð Nondeterministic systems ð Hierarchical Rationality ð Bargaining and Coalitions ð Multilevel modeling of uncertainty ð Multilevel simulation of uncertainty ð Demand Interfaces ð Corporate attitudes

7. Motivation for Flexible Systems Multicriteria decision making under certainty ENTERPRISE UNAWARENESS ORGANIZATIONAL UNCONSCIOUS Single criteria decision making under un/certainty Multicriteria decision making under uncertainty Single criteria decision making under un/certainty ORGANIZATIONAL CONSCIOUS ENTERPRISE AWARENESS Good: Customer and engineering attributes Bad: Tradeoffs, lack of consensus Good: Bottom line prediction Bad: Difficult to initiate and maintain

8. Flexible Systems  Can adapt themselves to meet a variety of requirements  Combines engineers’ ability to meet technical and customer requirements while assessing demand and profit.

9. a Center of Gravity KRKR KFKF FRONT ClRClR ClFClF Simplified Formula 1 Racing Model (w/ industrial partner: Milliken Research Associates) Flexible System Example: Racecar Design 8.88.858.98.9599.059.19.159.2 16 16.2 16.4 16.6 16.8 17 17.2 17.4 17.6 17.8 11 Time for 1 Lap on 100' Radius (sec) Time for 1 Lap on 840' Radius (sec) Simulation Results for 2 race tracks Best Set of Vehicle Designs Indianapolis Motor Speedway Multiple performance attributes (course sections)

10. 0.580.60.620.640.660.68 0.25 0.35 0.45 0.55 0.65 0.75 Optimal Racecar Designs Normalized Longitudinal CG Location Normalized Front Roll Stiffness * * Region of Optimal Flexibility - Racecar can be tuned depending upon the race course

11. Wrap-up How should the preferences of end users, product designers, and company managers be captured in engineering design? What should be the role of multi-criteria decision making approach vs. single-criterion approach? What do you see as the top research issues for this topic in particular and for Decision-Based Design in general? States of consciousness dependent Previous few slides By increasing the level of organizational consciousness